






'''simple docstring'''





import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List

import git
import torch
from torch.utils.data import Dataset

from transformers import BartTokenizer, RagTokenizer, TaTokenizer



def        __snake_case						(__UpperCAmelCase       ,	__UpperCAmelCase       ,	__UpperCAmelCase       ,	__UpperCAmelCase       ,	__UpperCAmelCase=True       ,	__UpperCAmelCase="pt"    ):





	"""simple docstring"""
	lowerCamelCase_					:  str						=    {'''add_prefix_space''': True} if isinstance(__UpperCAmelCase       ,	__UpperCAmelCase    ) and not line.startswith(''' '''    ) else {}
	lowerCamelCase_					:  Optional[Any]						=    padding_side
	return tokenizer(
	    [line]       ,	max_length=__UpperCAmelCase       ,	padding='''max_length''' if pad_to_max_length else None       ,	truncation=__UpperCAmelCase       ,	return_tensors=__UpperCAmelCase       ,	add_special_tokens=__UpperCAmelCase       ,	**__UpperCAmelCase       ,	)



def        __snake_case						(__UpperCAmelCase       ,	__UpperCAmelCase       ,	__UpperCAmelCase=None       ,	):





	"""simple docstring"""
	lowerCamelCase_					:  Optional[int]						=    input_ids.ne(__UpperCAmelCase    ).any(dim=0    )
	if attention_mask is None:
		return input_ids[:, keep_column_mask]
	else:
		return (input_ids[:, keep_column_mask], attention_mask[:, keep_column_mask])



class   lowerCAmelCase__ ( _lowerCAmelCase  ):

			def __init__(					self					:		List[str]     ,		UpperCamelCase_					:		Any     ,		UpperCamelCase_					:		Union[str, Any]     ,		UpperCamelCase_					:		int     ,		UpperCamelCase_					:		Optional[int]     ,		UpperCamelCase_					:		Optional[Any]="train"     ,		UpperCamelCase_					:		Optional[int]=None     ,		UpperCamelCase_					:		Tuple=None     ,		UpperCamelCase_					:		str=None     ,		UpperCamelCase_					:		Dict=""     ,		) ->  Dict:







				"""simple docstring"""






				super().__init__()
				lowerCamelCase_					:  List[Any]						=    Path(UpperCamelCase_	).joinpath(type_path + '''.source'''	)
				lowerCamelCase_					:  Any						=    Path(UpperCamelCase_	).joinpath(type_path + '''.target'''	)
				lowerCamelCase_					:  List[str]						=    self.get_char_lens(self.src_file	)
				lowerCamelCase_					:  Any						=    max_source_length
				lowerCamelCase_					:  List[str]						=    max_target_length
				assert min(self.src_lens	) > 0, F"""found empty line in {self.src_file}"""
				lowerCamelCase_					:  List[str]						=    tokenizer
				lowerCamelCase_					:  int						=    prefix
				if n_obs is not None:
					lowerCamelCase_					:  Dict						=    self.src_lens[:n_obs]
				lowerCamelCase_					:  Any						=    src_lang
				lowerCamelCase_					:  Optional[int]						=    tgt_lang

			def __len__(					self					:		Optional[Any]	) ->  List[str]:







				"""simple docstring"""






				return len(self.src_lens	)

			def __getitem__(					self					:		Any     ,		UpperCamelCase_					:		str	) ->  Dict[str, torch.Tensor]:







				"""simple docstring"""






				lowerCamelCase_					:  int						=    index + 1  # linecache starts at 1
				lowerCamelCase_					:  Any						=    self.prefix + linecache.getline(str(self.src_file	)     ,		UpperCamelCase_	).rstrip('''\n'''	)
				lowerCamelCase_					:  str						=    linecache.getline(str(self.tgt_file	)     ,		UpperCamelCase_	).rstrip('''\n'''	)
				assert source_line, F"""empty source line for index {index}"""
				assert tgt_line, F"""empty tgt line for index {index}"""

				# Need to add eos token manually for T5
				if isinstance(self.tokenizer     ,		UpperCamelCase_	):
					source_line += self.tokenizer.eos_token
					tgt_line += self.tokenizer.eos_token

				# Pad source and target to the right
				lowerCamelCase_					:  Dict						=    (
				    self.tokenizer.question_encoder if isinstance(self.tokenizer     ,		UpperCamelCase_	) else self.tokenizer
				)
				lowerCamelCase_					:  List[Any]						=    self.tokenizer.generator if isinstance(self.tokenizer     ,		UpperCamelCase_	) else self.tokenizer

				lowerCamelCase_					:  Tuple						=    encode_line(UpperCamelCase_     ,		UpperCamelCase_     ,		self.max_source_length     ,		'''right'''	)
				lowerCamelCase_					:  int						=    encode_line(UpperCamelCase_     ,		UpperCamelCase_     ,		self.max_target_length     ,		'''right'''	)

				lowerCamelCase_					:  Tuple						=    source_inputs['''input_ids'''].squeeze()
				lowerCamelCase_					:  str						=    target_inputs['''input_ids'''].squeeze()
				lowerCamelCase_					:  List[str]						=    source_inputs['''attention_mask'''].squeeze()
				return {
				    "input_ids": source_ids,
				    "attention_mask": src_mask,
				    "decoder_input_ids": target_ids,
				}

			@staticmethod
			def 						__UpperCamelCase				(					UpperCamelCase_					:		Tuple	) ->  Tuple:







				"""simple docstring"""






				return [len(UpperCamelCase_	) for x in Path(UpperCamelCase_	).open().readlines()]





			def 						__UpperCamelCase				(					self					:		str     ,		UpperCamelCase_					:		int	) ->  Dict[str, torch.Tensor]:







				"""simple docstring"""






				lowerCamelCase_					:  Any						=    torch.stack([x['''input_ids'''] for x in batch]	)
				lowerCamelCase_					:  int						=    torch.stack([x['''attention_mask'''] for x in batch]	)
				lowerCamelCase_					:  Tuple						=    torch.stack([x['''decoder_input_ids'''] for x in batch]	)
				lowerCamelCase_					:  List[Any]						=    (
				    self.tokenizer.generator.pad_token_id
				    if isinstance(self.tokenizer     ,		UpperCamelCase_	)
				    else self.tokenizer.pad_token_id
				)
				lowerCamelCase_					:  Tuple						=    (
				    self.tokenizer.question_encoder.pad_token_id
				    if isinstance(self.tokenizer     ,		UpperCamelCase_	)
				    else self.tokenizer.pad_token_id
				)
				lowerCamelCase_					:  Dict						=    trim_batch(UpperCamelCase_     ,		UpperCamelCase_	)
				lowerCamelCase_	,				lowerCamelCase_					:  int						=    trim_batch(UpperCamelCase_     ,		UpperCamelCase_     ,		attention_mask=UpperCamelCase_	)
				lowerCamelCase_					:  Any						=    {
				    '''input_ids''': source_ids,
				    '''attention_mask''': source_mask,
				    '''decoder_input_ids''': y,
				}
				return batch






__lowerCamelCase						:    Union[str, Any]     				=  getLogger(__name__)



def        __snake_case						(__UpperCAmelCase    ):





	"""simple docstring"""
	return list(itertools.chain.from_iterable(__UpperCAmelCase    )    )



def        __snake_case						(__UpperCAmelCase    ):





	"""simple docstring"""
	lowerCamelCase_					:  Optional[int]						=    get_git_info()
	save_json(__UpperCAmelCase       ,	os.path.join(__UpperCAmelCase       ,	'''git_log.json'''    )    )



def        __snake_case						(__UpperCAmelCase       ,	__UpperCAmelCase       ,	__UpperCAmelCase=4       ,	**__UpperCAmelCase    ):





	"""simple docstring"""







	with open(__UpperCAmelCase       ,	'''w'''    ) as f:
		json.dump(__UpperCAmelCase       ,	__UpperCAmelCase       ,	indent=__UpperCAmelCase       ,	**__UpperCAmelCase    )



def        __snake_case						(__UpperCAmelCase    ):





	"""simple docstring"""







	with open(__UpperCAmelCase    ) as f:
		return json.load(__UpperCAmelCase    )



def        __snake_case						():





	"""simple docstring"""
	lowerCamelCase_					:  str						=    git.Repo(search_parent_directories=__UpperCAmelCase    )
	lowerCamelCase_					:  Tuple						=    {
	    '''repo_id''': str(__UpperCAmelCase    ),
	    '''repo_sha''': str(repo.head.object.hexsha    ),
	    '''repo_branch''': str(repo.active_branch    ),
	    '''hostname''': str(socket.gethostname()    ),
	}
	return repo_infos



def        __snake_case						(__UpperCAmelCase       ,	__UpperCAmelCase    ):





	"""simple docstring"""
	return list(map(__UpperCAmelCase       ,	__UpperCAmelCase    )    )



def        __snake_case						(__UpperCAmelCase       ,	__UpperCAmelCase    ):





	"""simple docstring"""







	with open(__UpperCAmelCase       ,	'''wb'''    ) as f:
		return pickle.dump(__UpperCAmelCase       ,	__UpperCAmelCase    )



def        __snake_case						(__UpperCAmelCase    ):





	"""simple docstring"""







	def remove_articles(__UpperCAmelCase    ):
		return re.sub(R'''\b(a|an|the)\b'''       ,	''' '''       ,	__UpperCAmelCase    )

	def white_space_fix(__UpperCAmelCase    ):
		return " ".join(text.split()    )

	def remove_punc(__UpperCAmelCase    ):
		lowerCamelCase_					:  Union[str, Any]						=    set(string.punctuation    )
		return "".join(ch for ch in text if ch not in exclude    )

	def lower(__UpperCAmelCase    ):
		return text.lower()

	return white_space_fix(remove_articles(remove_punc(lower(__UpperCAmelCase    )    )    )    )



def        __snake_case						(__UpperCAmelCase       ,	__UpperCAmelCase    ):





	"""simple docstring"""
	lowerCamelCase_					:  Dict						=    normalize_answer(__UpperCAmelCase    ).split()
	lowerCamelCase_					:  Tuple						=    normalize_answer(__UpperCAmelCase    ).split()
	lowerCamelCase_					:  Union[str, Any]						=    Counter(__UpperCAmelCase    ) & Counter(__UpperCAmelCase    )
	lowerCamelCase_					:  int						=    sum(common.values()    )
	if num_same == 0:
		return 0
	lowerCamelCase_					:  int						=    1.0 * num_same / len(__UpperCAmelCase    )
	lowerCamelCase_					:  List[str]						=    1.0 * num_same / len(__UpperCAmelCase    )
	lowerCamelCase_					:  Optional[Any]						=    (2 * precision * recall) / (precision + recall)
	return fa



def        __snake_case						(__UpperCAmelCase       ,	__UpperCAmelCase    ):





	"""simple docstring"""
	return normalize_answer(__UpperCAmelCase    ) == normalize_answer(__UpperCAmelCase    )



def        __snake_case						(__UpperCAmelCase       ,	__UpperCAmelCase    ):





	"""simple docstring"""
	assert len(__UpperCAmelCase    ) == len(__UpperCAmelCase    )
	lowerCamelCase_					:  int						=    0
	for hypo, pred in zip(__UpperCAmelCase       ,	__UpperCAmelCase    ):
		em += exact_match_score(__UpperCAmelCase       ,	__UpperCAmelCase    )
	if len(__UpperCAmelCase    ) > 0:
		em /= len(__UpperCAmelCase    )
	return {"em": em}



def        __snake_case						(__UpperCAmelCase    ):





	"""simple docstring"""
	return model_prefix.startswith('''rag'''    )




def        __snake_case						(__UpperCAmelCase       ,	__UpperCAmelCase       ,	__UpperCAmelCase    ):





	"""simple docstring"""
	lowerCamelCase_					:  int						=    {p: p for p in extra_params}
	# T5 models don't have `dropout` param, they have `dropout_rate` instead
	lowerCamelCase_					:  Union[str, Any]						=    '''dropout_rate'''
	for p in extra_params:
		if getattr(__UpperCAmelCase       ,	__UpperCAmelCase       ,	__UpperCAmelCase    ):
			if not hasattr(__UpperCAmelCase       ,	__UpperCAmelCase    ) and not hasattr(__UpperCAmelCase       ,	equivalent_param[p]    ):
				logger.info('''config doesn\'t have a `{}` attribute'''.format(__UpperCAmelCase    )    )
				delattr(__UpperCAmelCase       ,	__UpperCAmelCase    )
				continue
			lowerCamelCase_					:  Union[str, Any]						=    p if hasattr(__UpperCAmelCase       ,	__UpperCAmelCase    ) else equivalent_param[p]
			setattr(__UpperCAmelCase       ,	__UpperCAmelCase       ,	getattr(__UpperCAmelCase       ,	__UpperCAmelCase    )    )
			delattr(__UpperCAmelCase       ,	__UpperCAmelCase    )
	return hparams, config












'''simple docstring'''







from torch import nn







def 						_A      ( UpperCAmelCase						):






   '''simple docstring'''







   if act_fn in ["swish", "silu"]:
      return nn.SiLU()
   elif act_fn == "mish":
      return nn.Mish()
   elif act_fn == "gelu":
      return nn.GELU()
   else:
      raise ValueError(F"""Unsupported activation function: {act_fn}"""						)


